朝着使用分支覆盖自动生成测试数据的方向发展

Jifeng Chen, Luming Yang
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引用次数: 1

摘要

分析了利用分支覆盖自动生成测试数据的各种方法,讨论了它们的特点和缺点,提出了一种新的自动生成测试数据的算法。该算法通过构建新的过程流程图,利用斐波那契定律对选择路径进行优化,并生成分配分支的测试数据。当所选路径的分支谓词为线性表示时,直接求解线性约束集生成测试数据,否则判定路径不可达;当分支谓词由非线性表达式组成时,利用分差近似导数对非线性函数进行线性化,保证通过简单迭代即可轻松生成试验数据,或在很大程度上得出路径不可达的结论。如果选择的路径在很大程度上不可达或不可达,则选择新的路径,重复上述过程,直到获得所需的数据,如果没有选择新的路径,则指定的分支不可达。实验证明了该算法的可行性和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards automatic generation of test data using branch coverage
By analyzing various methods of automatic generation of test data using branch coverage, their characteristics and disadvantages are discussed, a new algorithm for automatic generation of test data is proposed. Through constructing the new procedure flow chart, the algorithm optimizes the selection paths using Fibonacci law, and generates test data for assigned branch. When the branch predicates of the chosen path are linear representation, solve the linear restraint set directly to generate test data, otherwise determine that the path is inaccessible; When the branch predicate composing of nonlinear expression, linearize nonlinear function by using the divided difference approximate derivative to ensure the test data can easily generated through simple iteration, or conclude that path is inaccessible to a large extent. If the chosen path is to a large extent inaccessible or inaccessible, then a new path is selected, repeat the above process until the desired data obtained, if no new path was chosen, then the specified branch was inaccessible. Experiments show that the algorithm is feasible and valid.
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